Retail stores, particularly supermarkets, lose a significant amount of their inventory due to fraudulent activities in the front-end checkout area. These losses are a combination of employee fraud, customer fraud, and procedural error. Understandably, the retail industry is continuously striving for ways to prevent such fraudulent activities.
With the advent of product identification codes, such as the Universal Product Codes (UPCs), most point-of-sale transactions are performed automatically or semi-automatically. For example, in supermarket environments, customers place items to be purchased on a feed belt at a checkout counter. A checkout clerk (i.e., "checker") passes each item over a scanning device and then places the item on a take-away belt that moves the item to a bagging area. The scanning device "reads" the UPC label on the item and sends the item's identification code to a point-of-sale (POS) system. The POS system maintains a database containing product information for each UPC code, including a description of the item and its price. When the POS system receives a scanned UPC code, it displays a description of the scanned item and adds the item's price to the purchase total. POS systems perform a number of other functions, including store inventory and accounting functions.
One form of customer fraud that can result in substantial losses for a supermarket involves removing the UPC label of a lower priced item and placing it over the UPC label of a more expensive item. At a checkout counter, unless the checker reads the description of each item after it is scanned, which is rarely the case, the customer will not be charged the true price of the item. Similar losses can occur if a store employee inadvertently misapplies the UPC code of a lower priced item to a higher priced item. A standard POS system simply cannot determine at the point of sale whether a UPC label has been deliberately or inadvertently misapplied to an item.
Unscrupulous checkout clerks can conspire with customers to defraud a store by failing to pass items over the UPC scanner before placing them on the take-away belt. Also, a checker can position a higher priced item on top of a lower priced item, scan only the lower priced item, and then place both items on the take-away belt. These and other methods of deceit can result in significant losses. Accordingly, systems and methods are needed for preventing fraud in retail checkout environments.
Schneider, U.S. Pat. No. 5,115,888, discloses a self-service checkout system in which customers perform scanning and bagging of items themselves at automated checkout counters. Once a customer has scanned all items to be purchased, the customer proceeds to a central area for payment. Such systems are intended to reduce the number of store personnel required for checkout operations. In an effort to prevent fraud, the customer is required to place each item on a scale after scanning the item's identification code. The scanned identification code and measured weight of the item are then transmitted to a computer that contains a database of expected weights for each unique product code so that the computer can verify the measured weight against the expected weight for the scanned item. If the measured and expected weights do not match within an acceptable tolerance, an alert is issued to a supervisory employee who may then review the transaction more closely. A video camera is positioned at each automated checkout counter so that a supervisory employee can review selected transactions from a remote location.
Humble et al., U.S. Pat. No. 4,792,018, discloses a similar operator-unattended checkout system in which both weight and shape of an item are verified against the scanned product code. The shape of an item is discerned as it passes through a light curtain; essentially a silhouette of the item is obtained. A database in the system contains expected weight and shape characteristics for each unique product code. A discrepancy between the measured and expected characteristics will cause the item to be rejected.
While the systems of Humble et al. and Schneider provide some degree of security against customer fraud, the use of weight and/or shape characteristics to differentiate purchased items is unacceptable in most practical applications. Supermarkets can have inventories of more than 30,000 different items. Such a large number of items cannot be adequately differentiated based on weight and shape characteristics alone. For example, two different frozen dinner products (i.e., "TV dinners") may have identical weight and shape characteristics, but one may be significantly more expensive than the other. Consequently, security systems and methods capable of a much higher degree of product differentiation are needed to overcome the limitations of the aforementioned prior art systems. The system and methods of the present invention satisfy this need.